• Journal of Institute of Control, Robotics and Systems
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• v.22 no.1
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• pp.24-30
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• 2016

The accuracy of small and low-cost CCD cameras is insufficient to provide data for precisely tracking unmanned aerial vehicles (UAVs). This study shows how a quad rotor UAV can hover on a human targeted tracking object by using data from a CCD camera rather than imprecise GPS data. To realize this, quadcopter UAVs need to recognize their position and posture in known environments as well as unknown environments. Moreover, it is necessary for their localization to occur naturally. It is desirable for UAVs to estimate their position by solving uncertainty for quadcopter UAV hovering, as this is one of the most important problems. In this paper, we describe a method for determining the altitude of a quadcopter UAV using image information of a moving object like a walking human. This method combines the observed position from GPS sensors and the estimated position from images captured by a fixed camera to localize a UAV. Using the a priori known path of a quadcopter UAV in the world coordinates and a perspective camera model, we derive the geometric constraint equations that represent the relation between image frame coordinates for a moving object and the estimated quadcopter UAV's altitude. Since the equations are based on the geometric constraint equation, measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the quadcopter UAV. The Kalman filter scheme is applied for this method. Its performance is verified by a computer simulation and experiments.

• Korean Journal of Agricultural Science
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• v.42 no.3
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• pp.269-276
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• 2015

Unmanned Aerial Vehicle (UAV) has several advantages over conventional remote sensing techniques. They can acquire high-resolution images quickly and repeatedly. And with a comparatively lower flight altitude, they can obtain good quality images even in cloudy weather. In this paper, we discussed the state-of-the-art of the domestic and international use of UAV in agricultural sector as well as assessed its utilization and applicability for agricultural environment in Korea. Association of robotic, computer vision and geomatic technologies have established a new paradigm of low-altitude aerial remote sensing that has now been receiving attention from researchers all over the world. In a field study, it has been found that use of UAV imagery in an agricultural subsidy program can reduce the farmers' complain and provide objective evidence. UAV high resolution photography can also be helpful in monitoring the disposal zone for animal carcasses. Due to its expeditiousness and accuracy, UAV imagery can be a very useful tool to evaluate the damage in case of an agricultural disaster for both parties insurance companies and the farmers. Also high spatial and temporal resolution in UAV system can increase the prediction accuracy which in turn help to maintain the agricultural supply and demand chain.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1052-1054
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• 2003

RAZAKSAT is a second micro-satellite mission by Malaysian Satellite Program and is expected for launch in June 2004. Designed to orbit the earth at low-equatorial orbit, RAZAKSAT will meet Malaysia’s immediate needs to rapid data acquisition (real time and more repetitions) to address many operational issues of remote sensing applications, which require availability of current data sets. RAZAKSAT will be among the first remote sensing satellite to orbit the earth at low inclination along the equator, 9$^{\circ}$ with 685km altitude, hence, allows optimal geographical information and environment change within equatorial region be observed with a unique revisit characteristics. The satellite primary payload is MAC, a push-broom type camera with 2.5m of ground sampling distance (GSD) in panchromatic band and 5m of GSD in four multi-spectral bands. This paper describes on the variation of illumination anticipated from simulated RAZAKSAT image, examine its implication to its ground leaving radiances for major applications.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.1
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• pp.1-14
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• 2020

In this study, we 1) identified the damaged areas along the south limit line (SLL) of the demilitarized zone (DMZ) by the military's 'DMZ barren land campaign', and 2) categorized the identified damaged areas into a few ecological types. Using high-resolution satellite images, we delineated the total damaged areas to be 1,183.2 ha, which accounted for 50.1% of the 100-m northern buffer regions from the SLL. Of the total damaged areas, 16% were severely damaged, i.e., they had been damaged until recently and so remained barren without vegetation cover. In other areas, the levels of damage were either moderate (59.9%) or slight (24.1%), due to natural succession that turned those areas to grassland or forest. Using satellite image-derived land cover maps and climatic and topographic data, we categorized the damaged areas into seven types: lowland grassland (19.8%), western lowland forest (21.4%), low-altitude forest (25.5%), mid-altitude forest (18.4%), high-altitude forest (6.8%), vicinity in east coast (7.9%), and waterbody (0.2%). These types can be used to identify proper measures to restore ecosystems in the DMZ for now and after Korean reunification.

• Journal of Advanced Navigation Technology
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• v.22 no.4
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• pp.295-301
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• 2018

Recently, GPS(Global Positioning System) array antenna technology is generally used and widely adopted as a national infrastructure structure and aero-vehicles for protection the GPS signal reception. Until now, the 2-dimensional planar array is universally used for its applications in the array antenna signal processing, however relatively higher altitude air vehicles such as UAV experiences additional null zones induced by low altitude GPS interferences which is located in a symmetry zone of antenna horizontal plane and this could make the receiving antenna pattern coverage reduction. In this paper, we improved 20% of the beam pattern receiving performance and 13 dB correlation value improvement by eliminating the interference mirror images.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.7
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• pp.576-585
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• 2014

In this paper, we survey the Moving Target Indication(MTI) techniques for small UAVs. MTI consists of image alignment phase and frame differencing correction phase, and image alignment has two ways of parametric approach which is mainly focused in this paper and non-parametric approach. Since small UAVs are operated in the low altitude, the parallax is considerable and the epipolar geometry is applied to compensate the parallax. The related works and future works are presented.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.6
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• pp.91-97
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• 2015

The Unmanned Aerial Vehicles (UAVs) have several advantages over conventional RS techniques. They can acquire high-resolution images quickly and repeatedly. And with a comparatively lower flight altitude i.e. 80~400 m, they can obtain good quality images even in cloudy weather. Therefore, they are ideal for acquiring spatial data in cases of small agricultural field with mixed crop, abundant in South Korea. This paper discuss the use of low cost UAV based remote sensing for classifying crops. The study area, Gochang is produced by several crops such as red pepper, radish, Chinese cabbage, rubus coreanus, welsh onion, bean in South Korea. This study acquired images using fixed wing UAV on September 23, 2014. An object-based technique is used for classification of crops. The results showed that scale 250, shape 0.1, color 0.9, compactness 0.5 and smoothness 0.5 were the optimum parameter values in image segmentation. As a result, the kappa coefficient was 0.82 and the overall accuracy of classification was 85.0 %. The result of the present study validate our attempts for crop classification using high resolution UAV image as well as established the possibility of using such remote sensing techniques widely to resolve the difficulty of remote sensing data acquisition in agricultural sector.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.3-8
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• 2016

Due to the recent technical development and the enhancement of image resolution, Unmanned Airborne Vehicles(UAVs) have been used for various fields. A low altitude UAV system takes advantage of taking riverbed imagery at small rivers as well as land surface imagery on the ground. The bathymetric data are generated from the low altitude UAV system. The accuracy of the data is analyzed along water depths, comparing GPS observations and a DSM generated from UAV images. It is found that the depth accuracy of the geospatial data below 50 cm depth of water satisfies the regulation(${\pm}10cm$ spatial accuracy) of bathymetric surveying. Therefore this research shows that the geospatial data generated from UAV images at shallow regions of rivers can be used for bathymetric surveying.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.5 no.4
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• pp.789-796
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• 2015

The first phase of architecture design is the field survey of the site and its surroundings. To gather the information there are two methods :the traditional method of an onsite survey, and recently using 3D geometry data and high quality image mapping from online services such as Google Earth. However, the urban condition is fast changing, and information from online services may lack sufficient information. This paper presents the to fast and effective site survey method for urban site using an affordable and fully automated UAV for the architectural design field.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1224-1242
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• 2018

Aiming at motion analysis and compensation, it is essential to conduct motion detection with images. However, motion detection and tracking from low-altitude images obtained from an unmanned aerial system may pose many challenges due to degraded image quality caused by platform motion, image instability and illumination fluctuation. This research tackles these challenges by proposing a modified joint transform correlation algorithm which includes two preprocessing strategies. In spatial domain, a modified fuzzy edge detection method is proposed for preprocessing the input images. In frequency domain, to eliminate the disturbance of self-correlation items, the cross-correlation items are extracted from joint power spectrum output plane. The effectiveness and accuracy of the algorithm has been tested and evaluated by both simulation and real datasets in this research. The simulation experiments show that the proposed approach can derive satisfactory peaks of cross-correlation and achieve detection accuracy of displacement vectors with no more than 0.03pixel for image pairs with displacement smaller than 20pixels, when addition of image motion blurring in the range of 0~10pixel and 0.002variance of additive Gaussian noise. Moreover,this paper proposes quantitative analysis approach using tri-image pairs from real datasets and the experimental results show that detection accuracy can be achieved with sub-pixel level even if the sampling frequency can only attain 50 frames per second.